Collections / Differential Activity of MAPK signalling Defines Fibroblast Subtypes in Pancreatic Cancer (Spatial Transcriptomics)

Differential Activity of MAPK signalling Defines Fibroblast Subtypes in Pancreatic Cancer (Spatial Transcriptomics)

Fibroblast heterogeneity is increasingly recognised across cancer conditions. Given their important contribution to disease progression, mapping fibroblasts’ heterogeneity is critical to devise effective anti-cancer therapies. Cancer-associated fibroblasts (CAFs) represent the most abundant cell population in pancreatic ductal adenocarcinoma (PDAC). Whether CAF phenotypes are differently specified by PDAC cell lineages remains to be elucidated. Here, we reveal an important role for the MAPK signalling pathway in defining PDAC CAF phenotypes. We show that epithelial MAPK activity promotes the myofibroblastic differentiation of CAFs by sustaining the expression and secretion of TGF-β1. We integrate single-cell profiling of post-perturbation transcriptional responses from mouse models with cellular and spatial profiles of human tissues to define a MAPKhigh CAF (mapCAF) phenotype. We show that this phenotype associates with basal-like tumour cells and reduced frequency of CD8+ T cells. In addition to elevated MAPK activity, this mapCAF phenotype is characterized by TGF-b signalling, hypoxia responsive signatures, and immunoregulatory gene programs. Furthermore, the mapCAF signature is enriched in myofibroblastic CAFs from various cancer conditions and correlates with reduced response to immune checkpoint inhibition in melanoma Altogether, our data expand our knowledge on CAF phenotype heterogeneity and reveal a potential strategy for targeting of myofibroblastic CAFs in vivo.

Datasets4
Size~201 MB
AssayVisium
Samplehuman · pancreas
KindOther
Flag a data issue
PMID:39627211 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse274665")
cohort.members        # the 4 datasets as a table

print(cohort.licenses())              # check the terms before you download

sdatas = cohort.to_dict()             # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")
Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse274665")
coll.ordered_artifacts.to_dataframe()   # the 4 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse274665 --dest data/

Licenses: 4 NCBI GEO policy

Open in Vitessce
Visium
Human pancreas
GSM8454387
human pancreas pancreatic ductal adenocarcinoma 40.3 MB 2,234 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuepancreas
Conditionpancreatic ductal adenocarcinoma
Size40.3 MB
Spots2,234
Magnificationother · 3.972 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human pancreas
GSM8454388
human pancreas pancreatic ductal adenocarcinoma 64.2 MB 4,118 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuepancreas
Conditionpancreatic ductal adenocarcinoma
Size64.2 MB
Spots4,118
Magnificationother · 3.968 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human pancreas
GSM8454389
human pancreas pancreatic ductal adenocarcinoma 56.6 MB 2,932 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuepancreas
Conditionpancreatic ductal adenocarcinoma
Size56.6 MB
Spots2,932
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human pancreas
GSM8454390
human pancreas pancreatic ductal adenocarcinoma 40.0 MB 3,966 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuepancreas
Conditionpancreatic ductal adenocarcinoma
Size40.0 MB
Spots3,966
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-024-54975-8 ↗
BibTeX
@article{Veghini_2024,
  title = {Differential activity of MAPK signalling defines fibroblast subtypes in pancreatic cancer},
  volume = {15},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-024-54975-8},
  DOI = {10.1038/s41467-024-54975-8},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Veghini, Lisa and Pasini, Davide and Fang, Rui and Delfino, Pietro and Filippini, Dea and Neander, Christian and Vicentini, Caterina and Fiorini, Elena and Lupo, Francesca and D’Agosto, Sabrina L. and Carbone, Carmine and Agostini, Antonio and Piro, Geny and Rosa, Diego and Bevere, Michele and Markus, Peter and Behrens, Diana and Luchini, Claudio and Lawlor, Rita T. and Scarpa, Aldo and Biffi, Giulia and Cheung, Phyllis F. and Siveke, Jens T. and Corbo, Vincenzo},
  year = {2024},
  month = Dec
}